Deep Drowsiness Detection using YOLO, Pytorch and Python
Want to leverage YOLO object detection for safety?
One great implementation is using it to determine when drivers might be feeling a little drowsy. In this video we’re going to do exactly that using a fine tuned, customer object detection model powered by YOLO and PyTorch!
In this video you’ll learn how to:
- Instal Ultralytics YOLOv5
- Detect Objects from Images
- Detect Objects from Pre-Recorded Videos
- Detect Objects in Real Time Using OpenCV
- Fine Tuning a Drowsiness Model using YOLOv5 and PyTorch
- Perform Real Time Drowsiness Detection
Get the code:
GitHub: https://github.com/nicknochnack/YOLO-Drowsiness-Detection
Chapters
0:00 - Start
0:48 - Introduction
1:18 - Gameplan
2:23 - How it Works
3:05 - Tutorial Start
4:12 - 1. Install and Import Dependencies
10:51 - 2. Load Model
13:44 - 3. Make Detections using Images
21:05 - 4. Real Time Detections and Object Detection using Videos
30:05 - 5. Train a Custom YOLO Model
1:10:28 - 6. Detecting Drowsiness
1:17:58 - Ending
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